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    Producing and Study on Properties of TiB2–TiC–Al2O3 Composite Prepared by Mechanically Activated SHS Method

    , M.Sc. Thesis Sharif University of Technology Amini Rad, Sepideh (Author) ; Youzbashizadeh, Hossein (Supervisor)
    Abstract
    Metal matrix composites (MMCs) reinforced with ceramic particulates have been attractive as high specific strength materials utilized in automobile and aerospace industries. In order to enhance refinement and dispersibility of the ceramic particulates, the synthesis process with in-situ reactions has been investigated. The in-situ synthesis can avoid complexity and harmfulness.processes of powder handling and produce fine inclusions in the matrix with rather lower costs than conventional fabrication methods. In this study, the Al-based composites with TiC, TiB2 and Al2O3 particulates have been prepared by the by mechanically activated self-propagating high-temperature synthesis (MASHS) on... 

    Seizure Detection in Generalized and Focal Seizure from EEG Signals

    , M.Sc. Thesis Sharif University of Technology Mozafari, Mohsen (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    Epilepsy is one of the diseases that affects the quality of life of epileptic patients. Epileptic patients lose control during epileptic seizures and are more likely to face problems. Designing and creating a seizure detection system can reduce casualties from epileptic attacks. In this study, we present an automatic method that reduces the artifact from the raw signals, and then classifies the seizure and non-seizure epochs. At all stages, it is assumed that no information is available about the patient and this detection is made only based on the information of other patients. The data from this study were recorded in Temple Hospital and the recording conditions were not controlled, so... 

    Emotion Recognition from EEG Signals using Tensor based Algorithms

    , M.Sc. Thesis Sharif University of Technology Einizadeh, Aref (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    The brain electrical signal (EEG) has been widely used in clinical and academic research, due to its ease of recording, non-invasiveness and precision. One of the applications can be emotion recognition from the brain's electrical signal. Generally, two types of parameters (Valence and Arousal) are used to determine the type of emotion, which, in turn, indicate "positive or negative" and "level of extroversion or excitement" for a specific emotion. The significance of emotion is determined by the effects of this phenomenon on daily tasks, especially in cases where the person is confronted with activities that require careful attention and concentration.In the emotion recognition problem,... 

    Evaluation Auditory Attention Using Eeg Signals when Performing Motion and Visual Tasks

    , M.Sc. Thesis Sharif University of Technology Bagheri, Sara (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    Attention is one of the important aspects of brain cognitive activities, which has been widely discussed in psychology and neuroscience and is one of the main fields of research in the education field. The human sense of hearing is very complex, impactful and crucial in many processes such as learning. Human body always does several tasks and uses different senses simultaneously. For example, a student who listens to his/her teacher in the class, at the same time pays attention to the teacher, looks at a text or image, and sometimes writes a note.Using the electroencephalogram (EEG) signal for attention assessment and other cognitive activities is considered because of its facile recording,... 

    Studying Time Perception in Musician and Non-musician Using Auditory Stimuli

    , M.Sc. Thesis Sharif University of Technology Niroomand, Niavash (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    Time perception is a concept that describes how a person interprets the duration of an event. Depending on the circumstances, people may feel that time passes quickly or slowly. So far, the understanding, comparison, and estimation of the time interval have been described using a simple model, a pacemaker accumulator, that is powerful in explaining behavioral and biological data. Also, the role of the frequency band, Contingent Negative Variation (CNV), and Event-Related Potential (ERP) components have been investigated in the passage of time and the perception of time duration. Still, the stimuli used in these studies were not melodic. Predicting is one of the main behaviors of the brain.... 

    Diagnosis of Depressive Disorder using Classification of Graphs Obtained from Electroencephalogram Signals

    , M.Sc. Thesis Sharif University of Technology Moradi, Amir (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    Depression is a type of mental disorder that is characterized by the continuous occurrence of bad moods in the affected person. Studies by the World Health Organization (WHO) show that depression is the second disease that threatens human life, and eight hundred thousand people die due to suicide every year. In order to reduce the damage caused by depression, it is necessary to have an accurate method for diagnosing depression and its rapid treatment, in which electroencephalogram (EEG) signals are considered as one of the best methods for diagnosing depression. Until now, various researches have been conducted to diagnose depression using electroencephalogram signals, most of which were... 

    Inverse design of supersonic diffuser with flexible walls using a Genetic Algorithm

    , Article Journal of Fluids and Structures ; Volume 22, Issue 4 , 2006 , Pages 529-540 ; 08899746 (ISSN) Ziaei-Rad, S ; Ziaei-Rad, M ; Sharif University of Technology
    2006
    Abstract
    An efficient algorithm for the design optimization of the compressible fluid flow problem through a flexible structure is presented. The methodology has three essential parts: first the behavior of compressible flow in a supersonic diffuser was studied numerically in quasi-one-dimensional form using a flux splitting method. Second, a fully coupled sequential iterative procedure was used to solve the steady state aeroelastic problem of a flexible wall diffuser. Finally, a robust Genetic Algorithm was implemented and used to calculate the optimum shape of the flexible wall diffuser for a prescribed pressure distribution. © 2006 Elsevier Ltd. All rights reserved  

    Design and Implementation of a P300 Speller System by Using Auditory and Visual Paradigm

    , M.Sc. Thesis Sharif University of Technology Jalilpour, Shayan (Author) ; Hajipour Sardouie, Sepideh (Supervisor)
    Abstract
    The use of brain signals in controlling devices and communication with the external environment has been very much considered recently. The Brain-Computer Interface (BCI) systems enable people to easily handle most of their daily physical activity using the brain signal, without any need for movement. One of the most common BCI systems is P300 speller. In this type of BCI systems, the user can spell words without the need for typing with hands. In these systems, the electrical potential of the user's brain signals is distorted by visual, auditory, or tactile stimuli from his/her normal state. An essential principle in these systems is to exploit appropriate feature extraction methods which... 

    An Investigation of Resting-State Eeg Biomarkers Derived from Graph of Brain Connectivity for Diagnosis of Depressive Disorder

    , M.Sc. Thesis Sharif University of Technology Arabpour, Mohammad Reza (Author) ; Hajipour, Sepideh (Supervisor)
    Abstract
    Among the most costly diseases that affect a person's quality of life throughout his or her life, mental disorders (excluding sleep disorders) affect up to 25 percent of people in any community. One of the most common types of these disorders in Iran is depressive disorder, which according to official statistics, 13% of Iranians have some symptoms of it. Until now, the diagnosis of this disease has been traditionally done in clinics with interviews and questionnaires tests based on behavioral psychology and using symptom assessment. Therefore, there is a relatively low accuracy in the treatment process. Nowadays, with the help of functional brain imaging such as electroencephalogram (EEG)... 

    Extraction of Event Related Potentials (ERP) from EEG Signals using Semi-blind Approaches

    , M.Sc. Thesis Sharif University of Technology Jalilpour Monesi, Mohammad (Author) ; Hajipour Sardouie, Sepideh (Supervisor)
    Abstract
    Nowadays, Electroencephalogram (EEG) is the most common method for brain activity measurement. Event Related Potentials (ERP) which are recorded through EEG, have many applications. Detecting ERP signals is an important task since their amplitudes are quite small compared to the background EEG. The usual way to address this problem is to repeat the process of EEG recording several times and use the average signal. Though averaging can be helpful, there is a need for more complicated filtering. Blind source separation methods are frequently used for ERP denoising. These methods don’t use prior information for extracting sources and their use is limited to 2D problems only. To address these... 

    Design and Implementing an Evaluator Platforn for Cochlear Implent Devices

    , M.Sc. Thesis Sharif University of Technology Asadian, Saeed (Author) ; Hajipour, Sepideh (Supervisor) ; Molaei, Behnam (Co-Supervisor)
    Abstract
    The auditory system with its unique features has been considered by researchers in the past and its various parts from the outside of the body to its internal parts have been studied. The auditory nervous system, as the most important part of the auditory system, is responsible for receiving and processing information from the ear. The auditory system has different anatomical and physiological characteristics. The result of these characteristics is processing power in the field of time and frequency, which has received more attention in this dissertation. This processing power is most evident in the central auditory nervous system. This section includes nerve neurons and synapses from the... 

    Improving CCA Based Methods for SSVEP Classification using Graph Signal Processing

    , M.Sc. Thesis Sharif University of Technology Noori, Nastaran (Author) ; Hajipour Sardouie, Sepideh (Supervisor) ; Einizadeh, Aref (Co-Supervisor)
    Abstract
    The Brain Computer Interface (BCI) translates brain signals into a series of commands, enabling individuals to fulfill many of their basic needs without physical activity. Electroencephalogram (EEG) signals are commonly used as input for BCI systems, because the recording of this signal is non-invasive, inexpensive, and also have an acceptable time resolution. One of the most prevalent methods in BCI systems is the brain-computer interface based on Steady State Visual Evoked Potentials (SSVEP). These systems provide high response speed and Information Transfer Rate (ITR) as well as a good signal-to-noise ratio (SNR). The main purpose of these systems is to detect the frequency of SSVEP in... 

    Detection of High Frequency Oscillations from ECoG Recordings in Epileptic Patients

    , M.Sc. Thesis Sharif University of Technology Gharebaghi Asl, Fatemeh (Author) ; Hajipour, Sepideh (Supervisor) ; Sinaei, Farnaz (Co-Supervisor)
    Abstract
    The processing of brain signals, including the electrocorticogram (ECoG) signal, is widely used in the investigation of neurological diseases. Conventionally, the ECoG signal has frequency components up to the range of 80 Hz. Studies have proven that in some conditions, such as epilepsy, the brain signal includes frequency components higher than 80 Hz, which are called high-frequency oscillations (HFO). Therefore, HFOs are recognized as a biomarker for epilepsy. The aim of this thesis is to review the previous methods of detecting HFOs and to present new methods with greater efficiency in the direction of diagnosis or treatment of epileptic patients. For this purpose, we used the ECoG data... 

    Copper(II) acetate

    , Article Synlett ; Volume 23, Issue 13 , 2012 , Pages 1995-1996 ; 09365214 (ISSN) Amini, M ; Sharif University of Technology
    2012
    Abstract
    (A) Chakraborty and co-workers have developed a green method for the bulk ring-opening polymerization of lactides in the presence of Cu(OAc)2 as a good catalyst to synthesize polymers with different end-terminal groups.3 These polymerizations are highly controlled leading to the formation of polymers with the expected number of average molecular weights and narrow molecular weight distribution. (B) Garden and co-workers have found that the oxidative addition of anilines with 1,4-naphthoquinone to give N-aryl-2-amino-1,4-naphthoquinones can be performed in the presence of catalytic amounts of copper(II) acetate.4 All the reactions are generally more efficient in that they are cleaner, higher... 

    Solving rank one revised linear systems by the scaled ABS method

    , Article ANZIAM Journal ; Volume 46, Issue 2 , 2004 , Pages 225-236 ; 14461811 (ISSN) Amini, K ; Sharif University of Technology
    2004
    Abstract
    In mathematical programming, an important tool is the use of active set strategies to update the current solution of a linear system after a rank one change in the constraint matrix. We show how to update the general solution of a linear system obtained by use of the scaled ABS method when the matrix coefficient is subjected to a rank one change. © Australian Mathematical Society 2004  

    Modelling and Simulation of Melanoma Cancer, Based on Cellular Automata Approaches

    , M.Sc. Thesis Sharif University of Technology Rad, Jaber (Author) ; Habibi, Jafar (Supervisor)
    Abstract
    Nowadays, M&S is critical as a powerful tool for human to fight against cancer. Skin cancer is one of the most widespread cancers and melanoma would be the most dangerous kind of it. In cancerous micro-environment, cancer cells interact with vasculature, and compete with normal cells over nutrients. This plays a major role in tumor progression pattern and speed. In recent years, a few multiscale models have been developed considering these phenomena. Such a model provides a platform for future researches, especially in drug effects prediction. A reliable simulation must satisfy the constraints and facts in the real world as much as possible. M&S credibility assessment is a major concern to... 

    Automatic image annotation by a loosely joint non-negative matrix factorisation

    , Article IET Computer Vision ; Volume 9, Issue 6 , November , 2015 , Pages 806-813 ; 17519632 (ISSN) Rad, R ; Jamzad, M ; Sharif University of Technology
    Institution of Engineering and Technology  2015
    Abstract
    Nowadays, the number of digital images has increased so that the management of this volume of data needs an efficient system for browsing, categorising and searching. Automatic image annotation is designed for assigning tags to images for more accurate retrieval. Non-negative matrix factorisation (NMF) is a traditional machine learning technique for decomposing a matrix into a set of basis and coefficients under the non-negative constraints. In this study, the authors propose a two-step algorithm for designing an automatic image annotation system that employs the NMF framework for its first step and a variant of K-nearest neighbourhood as its second step. In the first step, a new multimodal... 

    A risk-based MILP approach for optimal placement of flammable gas detectors

    , Article Chemical Engineering Transactions ; Volume 53 , 2016 , Pages 145-150 ; 22839216 (ISSN) Rad, A ; Rashtchian, D ; Sharif University of Technology
    Italian Association of Chemical Engineering - AIDIC  2016
    Abstract
    Gas detectors play an important role in safety of process plants. In-time detection of flammable gas releases may prevent major fire and explosion as well as property loss in process plants. One of the challenges of the gas detection system design is determining the best layout for detectors in order to reduce the risk of gas releases as much as possible. However, current methods do not address the risk concept in placement of detectors quantitatively. A risk-based methodology is proposed for optimal placement of point type flammable gas detectors in which first the risk (defined as a combination of scenario frequency, delayed ignition probability and damage) is estimated for any release... 

    A multi-view-group non-negative matrix factorization approach for automatic image annotation

    , Article Multimedia Tools and Applications ; Volume 77, Issue 13 , 2018 , Pages 17109-17129 ; 13807501 (ISSN) Rad, R ; Jamzad, M ; Sharif University of Technology
    Springer New York LLC  2018
    Abstract
    In automatic image annotation (AIA) different features describe images from different aspects or views. Part of information embedded in some views is common for all views, while other parts are individual and specific. In this paper, we present the Mvg-NMF approach, a multi-view-group non-negative matrix factorization (NMF) method for an AIA system which considers both common and individual factors. The NMF framework discovers a latent space by decomposing data into a set of non-negative basis vectors and coefficients. The views divided into homogeneous groups and latent spaces are extracted for each group. After mapping the test images into these spaces, a unified distance matrix is... 

    A multi-view-group non-negative matrix factorization approach for automatic image annotation

    , Article Multimedia Tools and Applications ; 2017 , Pages 1-21 ; 13807501 (ISSN) Rad, R ; Jamzad, M ; Sharif University of Technology
    2017
    Abstract
    In automatic image annotation (AIA) different features describe images from different aspects or views. Part of information embedded in some views is common for all views, while other parts are individual and specific. In this paper, we present the Mvg-NMF approach, a multi-view-group non-negative matrix factorization (NMF) method for an AIA system which considers both common and individual factors. The NMF framework discovers a latent space by decomposing data into a set of non-negative basis vectors and coefficients. The views divided into homogeneous groups and latent spaces are extracted for each group. After mapping the test images into these spaces, a unified distance matrix is...